Qwen3.6-35B-A3B is a large language model from Alibaba's Qwen3.6 series, featuring a Mixture of Experts (MoE) architecture with 35 billion total parameters and approximately 3 billion active parameters per inference, delivering strong performance with efficient compute utilization. The model supports both thinking and non-thinking modes, offering flexible switching between rapid response and deep reasoning...

Qwen3.6-27B is the first open-weight small-to-mid-sized dense model in the Qwen3.6 series, with targeted improvements for code generation, agent workflows, and real-world development tasks. Compared with Qwen3.5-27B, it delivers clear gains in frontend development, repository-level reasoning, tool use, and complex problem solving, while adding support for preserving reasoning context across turns to reduce redundant reasoning in iterative workflows. It also supports vision understanding with a native context length of 262,144 tokens...

Qwen3.5-397B-A17B is the latest vision-language model in the Qwen series, featuring a Mixture-of-Experts (MoE) architecture with 397B total parameters and 17B activated parameters. It natively supports 256K context length, extensible to approximately 1M tokens, with support for 201 languages, unified vision-language understanding, tool calling, and reasoning (thinking) mode...

Qwen3.5-122B-A10B is a native multimodal large language model from the Qwen team, with 122B total parameters and only 10B activated. It features an efficient hybrid architecture combining Gated Delta Networks with sparse Mixture-of-Experts (MoE), natively supporting a 256K context length extensible up to ~1M tokens. Through early fusion training, it achieves unified vision-language capabilities supporting text, image, and video understanding, with strong performance across knowledge, reasoning, coding, agents, visual understanding, and multilingual benchmarks, surpassing GPT-5-mini and Qwen3-235B-A22B on multiple metrics. It defaults to thinking mode, supports tool calling, and covers 201 languages and dialects...

Qwen3.5-35B-A3B is a native multimodal large language model from the Qwen team, with 35B total parameters and only 3B activated. It features an efficient hybrid architecture combining Gated Delta Networks with sparse Mixture-of-Experts (MoE), natively supporting a 262K context length extensible up to ~1M tokens. The model achieves unified vision-language capabilities through early fusion training, supporting text, image, and video understanding with strong performance across reasoning, coding, agents, and visual understanding benchmarks. It defaults to thinking mode, supports tool calling, and covers 201 languages and dialects...

Qwen3.5-27B is a native multimodal large language model from the Qwen team with 27B parameters. It features an efficient hybrid architecture combining Gated Delta Networks with Gated Attention, natively supporting a 256K context length extensible up to ~1M tokens. The model achieves unified vision-language capabilities through early fusion training, supporting text, image, and video understanding with strong performance across reasoning, coding, agents, and visual understanding benchmarks, surpassing Qwen3-235B-A22B and GPT-5-mini on multiple metrics. It defaults to thinking mode, supports tool calling, and covers 201 languages and dialects...

Qwen3.5-9B is a native multimodal large language model from the Qwen team with 9B parameters. As a lightweight dense model in the Qwen3.5 series, it features an efficient hybrid architecture combining Gated Delta Networks with Gated Attention, natively supporting a 262K context length extensible up to ~1M tokens. The model achieves unified vision-language capabilities through early fusion training, supporting text, image, and video understanding. It defaults to thinking mode, supports tool calling, and covers 201 languages and dialects...

Qwen3-VL 是 Qwen3 系列中的 Vision-语言 模型，在各种 Vision-语言 (VL) 基准测试中实现了最先进的性能（SOTA）。该 模型 支持高分辨率 Image Input，最高可达百万像素级别，并拥有在一般视觉理解、多语言 OCR、细粒度视觉对齐和视觉对话方面的强大能力。作为 Qwen3 系列的一部分，它继承了强大的语言基础，使其能够理解和执行复杂的指令。...

Qwen3-VL-Thinking 是 Qwen3-VL 系列的一个版本，专为复杂的视觉推理任务进行了优化。它引入了“思考模式”，使其在提供最终答案之前能够生成详细的中间推理步骤（思维链条）。这种设计显著提升了模型在视觉问题回答（VQA）和其他需要多步逻辑、规划和深入分析的 Vision-语言任务上的表现。...

Qwen3-VL-8B-Instruct 是 Qwen3 系列的 Vision-语言模型，展示了在通用视觉理解、以视觉为中心的对话以及图像中多语言 Text 识别方面的强大能力。...

Qwen3-VL系列提供卓越的Text理解与生成、更深入的视觉感知与推理、扩展的上下文长度、增强的空间和Video动态理解能力，以及更强的代理互动能力。可用的Dense和MoE架构从边缘到云端扩展，还有指导和推理增强的Thinking版本。...

Qwen3-VL系列提供卓越的Text理解与生成、更深入的视觉感知与推理、扩展的上下文长度、增强的空间和Video动态理解能力，以及更强的代理互动能力。可用的Dense和MoE架构从边缘到云端扩展，还有指导和推理增强的Thinking版本。...

Qwen3-Coder-480B-A35B-Instruct is the most agentic code model released by Alibaba to date. It is a Mixture-of-Experts (MoE) model with 480 billion total parameters and 35 billion activated parameters, balancing efficiency and performance. The model natively supports a 256K (approximately 262,144) token context length, which can be extended up to 1 million tokens using extrapolation methods like YaRN, enabling it to handle repository-scale codebases and complex programming tasks. Qwen3-Coder is specifically designed for agentic coding workflows, where it not only generates code but also autonomously interacts with developer tools and environments to solve complex problems. It has achieved state-of-the-art results among open models on various coding and agentic benchmarks, with performance comparable to leading models like Claude Sonnet 4. Alongside the model, Alibaba has also open-sourced Qwen Code, a command-line tool designed to fully unleash its powerful agentic coding capabilities...

Qwen3-Coder-30B-A3B-Instruct 是由阿里巴巴的 Qwen 团队开发的 Qwen3 系列的一个代码模型。作为一个精简和优化的模型，它在提升编码能力的同时保持了令人印象深刻的性能和效率。它在复杂任务中表现出显著的性能优势，如 Agentic Coding、Agentic Browser-Use 和其他基础编码任务。该模型本地支持 256K token 的长上下文，可以扩展到 1M token，从而实现更好的库级理解和处理。此外，它为 Qwen Code 和 CLINE 等平台提供了强大的 Agentic 编码支持，具有专门设计的函数调用格式。...

Qwen3-30B-A3B-Instruct-2507 是 Qwen3-30B-A3B 非思考模式的更新版本。它是一个拥有 305 亿个总参数和 33 亿个激活参数的专家混合 (MoE) 模型。这个版本具有关键的增强功能，包括在指令遵循、逻辑推理、Text 理解、数学、科学、编码和工具使用等一般能力方面的显著改进。它还在多语言长尾知识覆盖方面显示出显著的提高，并在主观和开放式任务中与用户偏好有更好的对齐，能够提供更有帮助的响应和更高质量的 Text 生成。此外，它在长上下文理解方面的能力已增强至 256K。此模型仅支持非思考模式，并且不会在其 Output 中生成 `<think></think>` 块。...

Qwen3-32B是Qwen系列中的最新大型语言模型，拥有32.8B的参数。此模型独特地支持在思维模式（用于复杂逻辑推理、数学和编程）和非思维模式（用于高效的通用对话）之间无缝切换。它表现出显著增强的推理能力，超越了先前的QwQ和Qwen2.5 instruct模型在数学、代码生成和常识逻辑推理方面的表现。该模型在创意写作、角色扮演和多轮对话的人类偏好对齐方面表现出色。此外，它支持超过100种语言和方言，具有强大的多语言指令遵循和翻译能力...

Qwen3-14B 是 Qwen 系列中的最新大型语言模型，拥有 14.8B 参数。该模型独特地支持在思维模式（用于复杂的逻辑推理、数学和编程）和非思维模式（用于高效的通用对话）之间无缝切换。它展示了显著增强的推理能力，超越了之前的 QwQ 和 Qwen2.5 instruct 模型在数学、代码生成和常识性逻辑推理方面的表现。模型在人类偏好对齐方面表现出色，适用于创意写作、角色扮演和多轮对话。此外，它支持 100 多种语言和方言，具有强大的多语言指令跟随和翻译能力。...

Qwen3-8B是Qwen系列中最新的大型语言模型，具有8.2B参数。该模型独特地支持在思维模式（用于复杂的逻辑推理、数学和编码）和非思维模式（用于高效、通用的对话）之间无缝切换。它在推理能力上显著增强，超越了之前的QwQ和Qwen2.5指令模型，在数学、代码生成和常识逻辑推理方面表现出色。该模型在人类偏好对齐方面表现优异，适用于创意写作、角色扮演和多轮对话。此外，它支持100多种语言和方言，具有强大的多语言指令跟随和翻译能力。...

Qwen2.5-72B-Instruct 是阿里云发布的最新大型语言模型系列之一。72B 模型在编码和数学等领域表现出显著的改进。该模型还提供多语言支持，涵盖超过29种语言，包括中文和英语。它在遵循指令、理解结构化数据以及生成结构化 Output 方面显示出显著的改进，尤其是在 JSON 格式方面。...

Qwen2.5-7B-Instruct 是阿里云发布的最新大型语言模型系列之一。这个 7B 模型在编码和数学等领域表现出显著的改进。该模型还提供多语言支持，涵盖 29 种以上的语言，包括中文、英语等。模型在指令遵循、理解结构化数据和生成结构化 Output（特别是 JSON）方面显示出显著的增强。...